This paper is in the following e-collection/theme issue:

Serious Games for Health and Medicine (674) Emerging Technologies for Rehabilitation (256) Prosthetics and Neural Interfacing (5)

Published on in Vol 5, No 1 (2017): Jan-Mar

Game-Based Rehabilitation for Myoelectric Prosthesis Control

Game-Based Rehabilitation for Myoelectric Prosthesis Control

Game-Based Rehabilitation for Myoelectric Prosthesis Control

Authors of this article:

Cosima Prahm1 Author Orcid Image ;   Ivan Vujaklija2, 3 Author Orcid Image ;   Fares Kayali4 Author Orcid Image ;   Peter Purgathofer4 Author Orcid Image ;   Oskar C Aszmann1 Author Orcid Image
Article Authors Cited by (38) Tweetations (7) Metrics

Journals

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  3. Hashim N, Abd Razak N, Gholizadeh H, Abu Osman N. Video Game–Based Rehabilitation Approach for Individuals Who Have Undergone Upper Limb Amputation: Case-Control Study. JMIR Serious Games 2021;9(1):e17017 View
  4. Prahm C, Schulz A, Paaben B, Schoisswohl J, Kaniusas E, Dorffner G, Hammer B, Aszmann O. Counteracting Electrode Shifts in Upper-Limb Prosthesis Control via Transfer Learning. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2019;27(5):956 View
  5. Tobler-Ammann B, Surer E, de Bruin E, Rabuffetti M, Borghese N, Mainetti R, Pirovano M, Wittwer L, Knols R. Exergames Encouraging Exploration of Hemineglected Space in Stroke Patients With Visuospatial Neglect: A Feasibility Study. JMIR Serious Games 2017;5(3):e17 View
  6. Winslow B, Ruble M, Huber Z. Mobile, Game-Based Training for Myoelectric Prosthesis Control. Frontiers in Bioengineering and Biotechnology 2018;6 View
  7. Aman M, Festin C, Sporer M, Gstoettner C, Prahm C, Bergmeister K, Aszmann O. Bionic reconstruction. Wiener klinische Wochenschrift 2019;131(23-24):599 View
  8. Aguilar-Lazcano C, Rechy-Ramirez E, Hu H, Rios-Figueroa H, Marin-Hernandez A. Interaction Modalities Used on Serious Games for Upper Limb Rehabilitation: A Systematic Review. Games for Health Journal 2019;8(5):313 View
  9. Garske C, Dyson M, Dupan S, Nazarpour K. Perception of Game-Based Rehabilitation in Upper Limb Prosthetic Training: Survey of Users and Researchers. JMIR Serious Games 2021;9(1):e23710 View
  10. Boschmann A, Neuhaus D, Vogt S, Kaltschmidt C, Platzner M, Dosen S. Immersive augmented reality system for the training of pattern classification control with a myoelectric prosthesis. Journal of NeuroEngineering and Rehabilitation 2021;18(1) View
  11. Joyner J, Vaughn-Cooke M, Benz H. Comparison of Dexterous Task Performance in Virtual Reality and Real-World Environments. Frontiers in Virtual Reality 2021;2 View
  12. Heerschop A, van der Sluis C, Bongers R. Transfer of mode switching performance: from training to upper-limb prosthesis use. Journal of NeuroEngineering and Rehabilitation 2021;18(1) View
  13. Farina D, Vujaklija I, Brånemark R, Bull A, Dietl H, Graimann B, Hargrove L, Hoffmann K, Huang H, Ingvarsson T, Janusson H, Kristjánsson K, Kuiken T, Micera S, Stieglitz T, Sturma A, Tyler D, Weir R, Aszmann O. Toward higher-performance bionic limbs for wider clinical use. Nature Biomedical Engineering 2021;7(4):473 View
  14. Karczewski A, Dingle A, Poore S. The Need to Work Arm in Arm: Calling for Collaboration in Delivering Neuroprosthetic Limb Replacements. Frontiers in Neurorobotics 2021;15 View
  15. Gao S, Gong J, Chen B, Zhang B, Luo F, Yerabakan M, Pan Y, Hu B. Use of Advanced Materials and Artificial Intelligence in Electromyography Signal Detection and Interpretation. Advanced Intelligent Systems 2022;4(10) View
  16. Rossi F, Mongardi A, Ros P, Roch M, Martina M, Demarchi D. Tutorial: A Versatile Bio-Inspired System for Processing and Transmission of Muscular Information. IEEE Sensors Journal 2021;21(20):22285 View
  17. Gaballa A, Cavalcante R, Lamounier E, Soares A, Cabibihan J. Extended Reality “X-Reality” for Prosthesis Training of Upper-Limb Amputees: A Review on Current and Future Clinical Potential. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2022;30:1652 View
  18. Tabor A, Bateman S, Scheme E. Evaluation of Myoelectric Control Learning Using Multi-Session Game-Based Training. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2018;26(9):1680 View
  19. Peznola S, Gauthier L, Claypool M, Roop B, Lammert A. Compliance With In-Home Self-Managed Rehabilitation Post-Stroke is Largely Independent of Scheduling Approach. Archives of Physical Medicine and Rehabilitation 2023;104(4):554 View
  20. Garske C, Dyson M, Dupan S, Morgan G, Nazarpour K. Serious Games Are Not Serious Enough for Myoelectric Prosthetics. JMIR Serious Games 2021;9(4):e28079 View
  21. Muguro J, Laksono P, Rahmaniar W, Njeri W, Sasatake Y, Suhaimi M, Matsushita K, Sasaki M, Sulowicz M, Caesarendra W. Development of Surface EMG Game Control Interface for Persons with Upper Limb Functional Impairments. Signals 2021;2(4):834 View
  22. Raghibi L, Muhoza A, Evrard J, Ghazi H, van Oldeneel tot Oldenzeel G, Sonneville V, Macq B, Ronsse R. Virtual reality can mediate the learning phase of upper limb prostheses supporting a better-informed selection process. Journal on Multimodal User Interfaces 2023;17(1):33 View
  23. Li W, Shi P, Li S, Yu H. Current status and clinical perspectives of extended reality for myoelectric prostheses: review. Frontiers in Bioengineering and Biotechnology 2024;11 View
  24. Maas B, Van Der Sluis C, Bongers R. Assessing the effectiveness of serious game training designed to assist in upper limb prothesis rehabilitation. Frontiers in Rehabilitation Sciences 2024;5 View
  25. Calado A, Roselli P, Gruppioni E, Marinelli A, Bellingegni A, Boccardo N, Saggio G. A geometric algebra-based approach for myoelectric pattern recognition control and faster prosthesis recalibration. Expert Systems with Applications 2024;254:124373 View
  26. Maas B, Wright Z, Lock B, van der Sluis C, Bongers R. Using Serious Games to Measure Upper-Limb Myoelectric Pattern Recognition Prosthesis Control Performance in an At-Home Environment. JPO Journal of Prosthetics and Orthotics 2024;36(3):153 View
  27. Ma C, Nazarpour K. DistaNet: grasp-specific distance biofeedback promotes the retention of myoelectric skills. Journal of Neural Engineering 2024;21(3):036037 View

Books/Policy Documents

  1. Arcos Hurtado E, Ortegón Sanchez A, Rentería J, Castillo Garcia J, Millán Castro M. Applied Technologies. View
  2. Sime D. Biomedical Visualisation. View
  3. Prahm C, Vujaklija I, Kayali F, Sturma A. Bionic Limb Reconstruction. View
  4. Müller P, Achenbach P, Kleebe A, Schmitt J, Lehmann U, Tregel T, Göbel S. Serious Games. View
  5. Sturma A, Hruby L, Vujaklija I, Østlie K, Farina D. Bionic Limb Reconstruction. View
  6. Bahm J. Surgical Rationales in Functional Reconstructive Surgery of the Upper Extremity. View